Overview

Dataset statistics

Number of variables201
Number of observations103652
Missing cells0
Missing cells (%)0.0%
Duplicate rows56883
Duplicate rows (%)54.9%
Total size in memory159.0 MiB
Average record size in memory1.6 KiB

Variable types

Numeric5
Categorical196

Warnings

index__expense_0 has constant value "0.0" Constant
index__timesincelastevent_0 has constant value "0.0" Constant
index__timesincecasestart_0 has constant value "0.0" Constant
index__event_nr_0 has constant value "1.0" Constant
index__concept:name_0_Create Fine has constant value "1.0" Constant
index__lastSent_0_missing has constant value "1.0" Constant
index__notificationType_0_missing has constant value "1.0" Constant
Dataset has 56883 (54.9%) duplicate rows Duplicates
index__timesincemidnight_0 is highly correlated with index__hour_0High correlation
index__hour_0 is highly correlated with index__timesincemidnight_0High correlation
index__org:resource_0_840.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_9.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_819.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_807.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_115.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_551.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_847.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_213.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_191.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_843.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_842.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_855.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_193.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_557.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_813.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_34.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_831.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_823.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_561.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__concept:name_0_Create Fine is highly correlated with index__org:resource_0_840.0 and 194 other fieldsHigh correlation
index__org:resource_0_562.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__vehicleClass_A is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_3.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_838.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_54.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__dismissal_0_NIL is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_44.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_146.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_102.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_853.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_155.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_40.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_704.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_829.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_46.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_125.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_538.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_37.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_181.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_42.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_59.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_15.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_22.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_156.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_558.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__timesincelastevent_0 is highly correlated with index__org:resource_0_840.0 and 194 other fieldsHigh correlation
static__vehicleClass_R is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_844.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_833.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_15.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_850.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_36.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_190.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_827.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_841.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_14.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_18.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_55.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_536.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_835.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_563.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_47.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_553.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_40.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_24.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_33.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__event_nr_0 is highly correlated with index__org:resource_0_840.0 and 194 other fieldsHigh correlation
static__article_116.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__hour_0 is highly correlated with index__concept:name_0_Create Fine and 7 other fieldsHigh correlation
index__org:resource_0_53.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_851.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_568.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_20.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_49.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_4.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_7.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_846.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_143.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_60.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_552.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_830.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_141.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_97.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_849.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_825.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_834.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_94.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_43.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_566.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_other is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_541.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_45.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__dismissal_0_4 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_556.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_564.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_567.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_189.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_817.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_41.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_820.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_41.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_57.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_171.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_19.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_816.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_52.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_837.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_38.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__vehicleClass_C is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_832.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_23.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_554.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_39.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__vehicleClass_M is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_43.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__dismissal_0_@ is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_136.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_188.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_548.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__timesincecasestart_0 is highly correlated with index__org:resource_0_840.0 and 194 other fieldsHigh correlation
index__org:resource_0_852.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_11.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_31.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_845.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_824.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_20.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__timesincemidnight_0 is highly correlated with index__concept:name_0_Create Fine and 7 other fieldsHigh correlation
index__lastSent_0_missing is highly correlated with index__org:resource_0_840.0 and 194 other fieldsHigh correlation
index__expense_0 is highly correlated with index__org:resource_0_840.0 and 194 other fieldsHigh correlation
index__org:resource_0_25.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_51.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_808.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__dismissal_0_other is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_537.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_555.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_857.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__notificationType_0_missing is highly correlated with index__org:resource_0_840.0 and 194 other fieldsHigh correlation
index__org:resource_0_546.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_145.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_167.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_126.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_30.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_58.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_821.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_17.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_854.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__dismissal_0_D is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__dismissal_0_C is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_180.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_122.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_50.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_826.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_142.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_32.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_148.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_192.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_23.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_26.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_56.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_80.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_157.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_48.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_27.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_35.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_8.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_152.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_28.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_856.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_540.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_560.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_836.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_811.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_21.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_550.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_839.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_154.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_170.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_810.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_818.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_16.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_12.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_559.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_149.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_72.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_29.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_158.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_848.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_10.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_173.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_172.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_828.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_other is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_21.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_565.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__article_169.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
index__org:resource_0_802.0 is highly correlated with index__concept:name_0_Create Fine and 6 other fieldsHigh correlation
static__points has 101712 (98.1%) zeros Zeros
index__weekday_0 has 13632 (13.2%) zeros Zeros

Reproduction

Analysis started2021-04-14 22:51:20.321987
Analysis finished2021-04-14 23:07:33.963867
Duration16 minutes and 13.64 seconds
Software versionpandas-profiling v2.11.0
Download configurationconfig.yaml

Variables

static__amount
Real number (ℝ≥0)

Distinct78
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.19780178
Minimum0
Maximum4000
Zeros19
Zeros (%)< 0.1%
Memory size809.9 KiB
2021-04-15T01:07:34.022671image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile21
Q132.8
median35
Q336
95-th percentile125.19
Maximum4000
Range4000
Interquartile range (IQR)3.2

Descriptive statistics

Standard deviation44.47058738
Coefficient of variation (CV)1.029464129
Kurtosis748.3674251
Mean43.19780178
Median Absolute Deviation (MAD)1.4
Skewness15.96381752
Sum4477538.55
Variance1977.633142
MonotocityNot monotonic
2021-04-15T01:07:34.140631image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3521592
20.8%
3615840
15.3%
33.615339
14.8%
31.310784
10.4%
32.88538
 
8.2%
327136
 
6.9%
383981
 
3.8%
211662
 
1.6%
221522
 
1.5%
125.191380
 
1.3%
Other values (68)15878
15.3%
ValueCountFrequency (%)
019
 
< 0.1%
18.781252
1.2%
19528
0.5%
19.681001
1.0%
19.95826
0.8%
ValueCountFrequency (%)
40001
 
< 0.1%
18421
 
< 0.1%
1626.451
 
< 0.1%
77912
 
< 0.1%
74235
< 0.1%

static__points
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.06680044765
Minimum0
Maximum10
Zeros101712
Zeros (%)98.1%
Memory size809.9 KiB
2021-04-15T01:07:34.245754image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.548217065
Coefficient of variation (CV)8.206787294
Kurtosis114.8976249
Mean0.06680044765
Median Absolute Deviation (MAD)0
Skewness9.948698766
Sum6924
Variance0.3005419504
MonotocityNot monotonic
2021-04-15T01:07:34.326042image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0101712
98.1%
21037
 
1.0%
5739
 
0.7%
692
 
0.1%
1055
 
0.1%
39
 
< 0.1%
46
 
< 0.1%
12
 
< 0.1%
ValueCountFrequency (%)
0101712
98.1%
12
 
< 0.1%
21037
 
1.0%
39
 
< 0.1%
46
 
< 0.1%
ValueCountFrequency (%)
1055
 
0.1%
692
 
0.1%
5739
0.7%
46
 
< 0.1%
39
 
< 0.1%

static__article_102.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103649 
1.0
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103649
> 99.9%
1.03
 
< 0.1%
2021-04-15T01:07:34.496602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:34.554277image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103649
> 99.9%
1.03
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207301
66.7%
.103652
33.3%
13
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207301
> 99.9%
13
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207301
66.7%
.103652
33.3%
13
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207301
66.7%
.103652
33.3%
13
 
< 0.1%

static__article_115.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103646 
1.0
 
6

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103646
> 99.9%
1.06
 
< 0.1%
2021-04-15T01:07:34.700162image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:34.757160image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103646
> 99.9%
1.06
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207298
66.7%
.103652
33.3%
16
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207298
> 99.9%
16
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207298
66.7%
.103652
33.3%
16
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207298
66.7%
.103652
33.3%
16
 
< 0.1%

static__article_116.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103621 
1.0
 
31

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103621
> 99.9%
1.031
 
< 0.1%
2021-04-15T01:07:34.903252image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:34.960319image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103621
> 99.9%
1.031
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207273
66.7%
.103652
33.3%
131
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207273
> 99.9%
131
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207273
66.7%
.103652
33.3%
131
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207273
66.7%
.103652
33.3%
131
 
< 0.1%

static__article_122.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103648 
1.0
 
4

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103648
> 99.9%
1.04
 
< 0.1%
2021-04-15T01:07:35.107581image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:35.164799image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103648
> 99.9%
1.04
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207300
66.7%
.103652
33.3%
14
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207300
> 99.9%
14
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207300
66.7%
.103652
33.3%
14
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207300
66.7%
.103652
33.3%
14
 
< 0.1%

static__article_125.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103645 
1.0
 
7

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103645
> 99.9%
1.07
 
< 0.1%
2021-04-15T01:07:35.311110image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:35.367950image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103645
> 99.9%
1.07
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207297
66.7%
.103652
33.3%
17
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207297
> 99.9%
17
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207297
66.7%
.103652
33.3%
17
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207297
66.7%
.103652
33.3%
17
 
< 0.1%

static__article_126.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103633 
1.0
 
19

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103633
> 99.9%
1.019
 
< 0.1%
2021-04-15T01:07:35.514641image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:35.575626image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103633
> 99.9%
1.019
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207285
66.7%
.103652
33.3%
119
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207285
> 99.9%
119
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207285
66.7%
.103652
33.3%
119
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207285
66.7%
.103652
33.3%
119
 
< 0.1%

static__article_136.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103644 
1.0
 
8

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103644
> 99.9%
1.08
 
< 0.1%
2021-04-15T01:07:35.722564image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:35.779491image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103644
> 99.9%
1.08
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207296
66.7%
.103652
33.3%
18
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207296
> 99.9%
18
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207296
66.7%
.103652
33.3%
18
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207296
66.7%
.103652
33.3%
18
 
< 0.1%

static__article_141.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103592 
1.0
 
60

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103592
99.9%
1.060
 
0.1%
2021-04-15T01:07:35.926108image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:35.983487image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103592
99.9%
1.060
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207244
66.6%
.103652
33.3%
160
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207244
> 99.9%
160
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207244
66.6%
.103652
33.3%
160
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207244
66.6%
.103652
33.3%
160
 
< 0.1%

static__article_142.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
98702 
1.0
 
4950

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.098702
95.2%
1.04950
 
4.8%
2021-04-15T01:07:36.127324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:36.184494image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.098702
95.2%
1.04950
 
4.8%

Most occurring characters

ValueCountFrequency (%)
0202354
65.1%
.103652
33.3%
14950
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0202354
97.6%
14950
 
2.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0202354
65.1%
.103652
33.3%
14950
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0202354
65.1%
.103652
33.3%
14950
 
1.6%

static__article_143.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103614 
1.0
 
38

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103614
> 99.9%
1.038
 
< 0.1%
2021-04-15T01:07:36.334784image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:36.391860image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103614
> 99.9%
1.038
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207266
66.7%
.103652
33.3%
138
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207266
> 99.9%
138
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207266
66.7%
.103652
33.3%
138
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207266
66.7%
.103652
33.3%
138
 
< 0.1%

static__article_145.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103551 
1.0
 
101

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103551
99.9%
1.0101
 
0.1%
2021-04-15T01:07:36.538535image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:36.595209image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103551
99.9%
1.0101
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207203
66.6%
.103652
33.3%
1101
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207203
> 99.9%
1101
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207203
66.6%
.103652
33.3%
1101
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207203
66.6%
.103652
33.3%
1101
 
< 0.1%

static__article_146.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103468 
1.0
 
184

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103468
99.8%
1.0184
 
0.2%
2021-04-15T01:07:36.743777image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:36.800982image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103468
99.8%
1.0184
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207120
66.6%
.103652
33.3%
1184
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207120
99.9%
1184
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207120
66.6%
.103652
33.3%
1184
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207120
66.6%
.103652
33.3%
1184
 
0.1%

static__article_148.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103636 
1.0
 
16

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103636
> 99.9%
1.016
 
< 0.1%
2021-04-15T01:07:36.948575image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:37.005925image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103636
> 99.9%
1.016
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207288
66.7%
.103652
33.3%
116
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207288
> 99.9%
116
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207288
66.7%
.103652
33.3%
116
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207288
66.7%
.103652
33.3%
116
 
< 0.1%

static__article_149.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103622 
1.0
 
30

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103622
> 99.9%
1.030
 
< 0.1%
2021-04-15T01:07:37.153681image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:37.210751image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103622
> 99.9%
1.030
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207274
66.7%
.103652
33.3%
130
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207274
> 99.9%
130
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207274
66.7%
.103652
33.3%
130
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207274
66.7%
.103652
33.3%
130
 
< 0.1%

static__article_15.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103649 
1.0
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103649
> 99.9%
1.03
 
< 0.1%
2021-04-15T01:07:37.357018image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:37.413953image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103649
> 99.9%
1.03
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207301
66.7%
.103652
33.3%
13
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207301
> 99.9%
13
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207301
66.7%
.103652
33.3%
13
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207301
66.7%
.103652
33.3%
13
 
< 0.1%

static__article_152.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103650 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%
2021-04-15T01:07:37.564642image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:37.621414image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207302
> 99.9%
12
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

static__article_154.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103623 
1.0
 
29

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103623
> 99.9%
1.029
 
< 0.1%
2021-04-15T01:07:37.767613image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:37.824591image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103623
> 99.9%
1.029
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207275
66.7%
.103652
33.3%
129
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207275
> 99.9%
129
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207275
66.7%
.103652
33.3%
129
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207275
66.7%
.103652
33.3%
129
 
< 0.1%

static__article_155.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103641 
1.0
 
11

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103641
> 99.9%
1.011
 
< 0.1%
2021-04-15T01:07:37.978744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:38.035199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103641
> 99.9%
1.011
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207293
66.7%
.103652
33.3%
111
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207293
> 99.9%
111
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207293
66.7%
.103652
33.3%
111
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207293
66.7%
.103652
33.3%
111
 
< 0.1%

static__article_156.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103649 
1.0
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103649
> 99.9%
1.03
 
< 0.1%
2021-04-15T01:07:38.179810image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:38.236326image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103649
> 99.9%
1.03
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207301
66.7%
.103652
33.3%
13
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207301
> 99.9%
13
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207301
66.7%
.103652
33.3%
13
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207301
66.7%
.103652
33.3%
13
 
< 0.1%

static__article_157.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
1.0
53567 
0.0
50085 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0
ValueCountFrequency (%)
1.053567
51.7%
0.050085
48.3%
2021-04-15T01:07:38.392117image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:38.448689image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
1.053567
51.7%
0.050085
48.3%

Most occurring characters

ValueCountFrequency (%)
0153737
49.4%
.103652
33.3%
153567
 
17.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0153737
74.2%
153567
 
25.8%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0153737
49.4%
.103652
33.3%
153567
 
17.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0153737
49.4%
.103652
33.3%
153567
 
17.2%

static__article_158.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
87028 
1.0
16624 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.087028
84.0%
1.016624
 
16.0%
2021-04-15T01:07:38.604688image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:38.661594image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.087028
84.0%
1.016624
 
16.0%

Most occurring characters

ValueCountFrequency (%)
0190680
61.3%
.103652
33.3%
116624
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0190680
92.0%
116624
 
8.0%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0190680
61.3%
.103652
33.3%
116624
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0190680
61.3%
.103652
33.3%
116624
 
5.3%

static__article_167.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103650 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%
2021-04-15T01:07:38.807931image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:38.864379image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207302
> 99.9%
12
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

static__article_169.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103645 
1.0
 
7

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103645
> 99.9%
1.07
 
< 0.1%
2021-04-15T01:07:39.010438image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:39.067157image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103645
> 99.9%
1.07
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207297
66.7%
.103652
33.3%
17
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207297
> 99.9%
17
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207297
66.7%
.103652
33.3%
17
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207297
66.7%
.103652
33.3%
17
 
< 0.1%

static__article_170.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103574 
1.0
 
78

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103574
99.9%
1.078
 
0.1%
2021-04-15T01:07:39.215557image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:39.272608image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103574
99.9%
1.078
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207226
66.6%
.103652
33.3%
178
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207226
> 99.9%
178
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207226
66.6%
.103652
33.3%
178
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207226
66.6%
.103652
33.3%
178
 
< 0.1%

static__article_171.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103090 
1.0
 
562

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103090
99.5%
1.0562
 
0.5%
2021-04-15T01:07:39.419635image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:39.479599image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103090
99.5%
1.0562
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0206742
66.5%
.103652
33.3%
1562
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206742
99.7%
1562
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206742
66.5%
.103652
33.3%
1562
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206742
66.5%
.103652
33.3%
1562
 
0.2%

static__article_172.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103299 
1.0
 
353

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103299
99.7%
1.0353
 
0.3%
2021-04-15T01:07:39.626959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:39.683612image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103299
99.7%
1.0353
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0206951
66.6%
.103652
33.3%
1353
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206951
99.8%
1353
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206951
66.6%
.103652
33.3%
1353
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206951
66.6%
.103652
33.3%
1353
 
0.1%

static__article_173.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103614 
1.0
 
38

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103614
> 99.9%
1.038
 
< 0.1%
2021-04-15T01:07:39.832141image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:39.888727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103614
> 99.9%
1.038
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207266
66.7%
.103652
33.3%
138
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207266
> 99.9%
138
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207266
66.7%
.103652
33.3%
138
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207266
66.7%
.103652
33.3%
138
 
< 0.1%

static__article_180.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102957 
1.0
 
695

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102957
99.3%
1.0695
 
0.7%
2021-04-15T01:07:40.046687image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:40.103370image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102957
99.3%
1.0695
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0206609
66.4%
.103652
33.3%
1695
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206609
99.7%
1695
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206609
66.4%
.103652
33.3%
1695
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206609
66.4%
.103652
33.3%
1695
 
0.2%

static__article_181.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103291 
1.0
 
361

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103291
99.7%
1.0361
 
0.3%
2021-04-15T01:07:40.253738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:40.310383image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103291
99.7%
1.0361
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0206943
66.6%
.103652
33.3%
1361
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206943
99.8%
1361
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206943
66.6%
.103652
33.3%
1361
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206943
66.6%
.103652
33.3%
1361
 
0.1%

static__article_188.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103625 
1.0
 
27

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103625
> 99.9%
1.027
 
< 0.1%
2021-04-15T01:07:40.456632image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:40.513431image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103625
> 99.9%
1.027
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207277
66.7%
.103652
33.3%
127
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207277
> 99.9%
127
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207277
66.7%
.103652
33.3%
127
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207277
66.7%
.103652
33.3%
127
 
< 0.1%

static__article_189.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103645 
1.0
 
7

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103645
> 99.9%
1.07
 
< 0.1%
2021-04-15T01:07:40.659822image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:40.716778image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103645
> 99.9%
1.07
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207297
66.7%
.103652
33.3%
17
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207297
> 99.9%
17
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207297
66.7%
.103652
33.3%
17
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207297
66.7%
.103652
33.3%
17
 
< 0.1%

static__article_190.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103651 
1.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103651
> 99.9%
1.01
 
< 0.1%
2021-04-15T01:07:40.861546image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:40.918157image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103651
> 99.9%
1.01
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207303
66.7%
.103652
33.3%
11
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207303
> 99.9%
11
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207303
66.7%
.103652
33.3%
11
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207303
66.7%
.103652
33.3%
11
 
< 0.1%

static__article_191.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103586 
1.0
 
66

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103586
99.9%
1.066
 
0.1%
2021-04-15T01:07:41.063654image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:41.119867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103586
99.9%
1.066
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207238
66.6%
.103652
33.3%
166
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207238
> 99.9%
166
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207238
66.6%
.103652
33.3%
166
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207238
66.6%
.103652
33.3%
166
 
< 0.1%

static__article_192.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103650 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%
2021-04-15T01:07:41.265892image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:41.322352image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207302
> 99.9%
12
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

static__article_193.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103468 
1.0
 
184

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103468
99.8%
1.0184
 
0.2%
2021-04-15T01:07:41.467000image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:41.523499image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103468
99.8%
1.0184
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207120
66.6%
.103652
33.3%
1184
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207120
99.9%
1184
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207120
66.6%
.103652
33.3%
1184
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207120
66.6%
.103652
33.3%
1184
 
0.1%

static__article_20.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103539 
1.0
 
113

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103539
99.9%
1.0113
 
0.1%
2021-04-15T01:07:41.669564image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:41.726298image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103539
99.9%
1.0113
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207191
66.6%
.103652
33.3%
1113
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207191
99.9%
1113
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207191
66.6%
.103652
33.3%
1113
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207191
66.6%
.103652
33.3%
1113
 
< 0.1%

static__article_21.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103638 
1.0
 
14

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103638
> 99.9%
1.014
 
< 0.1%
2021-04-15T01:07:41.871522image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:41.930026image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103638
> 99.9%
1.014
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207290
66.7%
.103652
33.3%
114
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207290
> 99.9%
114
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207290
66.7%
.103652
33.3%
114
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207290
66.7%
.103652
33.3%
114
 
< 0.1%

static__article_213.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103650 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%
2021-04-15T01:07:42.075424image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:42.131763image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207302
> 99.9%
12
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

static__article_23.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103559 
1.0
 
93

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103559
99.9%
1.093
 
0.1%
2021-04-15T01:07:42.277218image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:42.333593image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103559
99.9%
1.093
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207211
66.6%
.103652
33.3%
193
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207211
> 99.9%
193
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207211
66.6%
.103652
33.3%
193
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207211
66.6%
.103652
33.3%
193
 
< 0.1%

static__article_40.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103647 
1.0
 
5

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103647
> 99.9%
1.05
 
< 0.1%
2021-04-15T01:07:42.478828image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:42.535402image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103647
> 99.9%
1.05
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207299
66.7%
.103652
33.3%
15
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207299
> 99.9%
15
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207299
66.7%
.103652
33.3%
15
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207299
66.7%
.103652
33.3%
15
 
< 0.1%

static__article_41.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103435 
1.0
 
217

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103435
99.8%
1.0217
 
0.2%
2021-04-15T01:07:42.682520image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:42.739045image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103435
99.8%
1.0217
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207087
66.6%
.103652
33.3%
1217
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207087
99.9%
1217
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207087
66.6%
.103652
33.3%
1217
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207087
66.6%
.103652
33.3%
1217
 
0.1%

static__article_43.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103358 
1.0
 
294

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103358
99.7%
1.0294
 
0.3%
2021-04-15T01:07:42.884940image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:42.942700image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103358
99.7%
1.0294
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0207010
66.6%
.103652
33.3%
1294
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207010
99.9%
1294
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207010
66.6%
.103652
33.3%
1294
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207010
66.6%
.103652
33.3%
1294
 
0.1%

static__article_7.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
79343 
1.0
24309 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.079343
76.5%
1.024309
 
23.5%
2021-04-15T01:07:43.089792image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:43.146137image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.079343
76.5%
1.024309
 
23.5%

Most occurring characters

ValueCountFrequency (%)
0182995
58.8%
.103652
33.3%
124309
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0182995
88.3%
124309
 
11.7%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0182995
58.8%
.103652
33.3%
124309
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0182995
58.8%
.103652
33.3%
124309
 
7.8%

static__article_72.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103644 
1.0
 
8

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103644
> 99.9%
1.08
 
< 0.1%
2021-04-15T01:07:43.293484image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:43.349952image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103644
> 99.9%
1.08
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207296
66.7%
.103652
33.3%
18
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207296
> 99.9%
18
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207296
66.7%
.103652
33.3%
18
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207296
66.7%
.103652
33.3%
18
 
< 0.1%

static__article_80.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103196 
1.0
 
456

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103196
99.6%
1.0456
 
0.4%
2021-04-15T01:07:43.495491image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:43.552264image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103196
99.6%
1.0456
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206848
66.5%
.103652
33.3%
1456
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206848
99.8%
1456
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206848
66.5%
.103652
33.3%
1456
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206848
66.5%
.103652
33.3%
1456
 
0.1%

static__article_94.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103631 
1.0
 
21

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103631
> 99.9%
1.021
 
< 0.1%
2021-04-15T01:07:43.700237image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:43.756663image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103631
> 99.9%
1.021
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207283
66.7%
.103652
33.3%
121
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207283
> 99.9%
121
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207283
66.7%
.103652
33.3%
121
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207283
66.7%
.103652
33.3%
121
 
< 0.1%

static__article_97.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103622 
1.0
 
30

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103622
> 99.9%
1.030
 
< 0.1%
2021-04-15T01:07:43.902371image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:43.960525image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103622
> 99.9%
1.030
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207274
66.7%
.103652
33.3%
130
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207274
> 99.9%
130
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207274
66.7%
.103652
33.3%
130
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207274
66.7%
.103652
33.3%
130
 
< 0.1%

static__article_other
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103641 
1.0
 
11

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103641
> 99.9%
1.011
 
< 0.1%
2021-04-15T01:07:44.107882image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:44.165001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103641
> 99.9%
1.011
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207293
66.7%
.103652
33.3%
111
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207293
> 99.9%
111
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207293
66.7%
.103652
33.3%
111
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207293
66.7%
.103652
33.3%
111
 
< 0.1%

static__vehicleClass_A
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
1.0
100952 
0.0
 
2700

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0
ValueCountFrequency (%)
1.0100952
97.4%
0.02700
 
2.6%
2021-04-15T01:07:44.314164image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:44.371244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
1.0100952
97.4%
0.02700
 
2.6%

Most occurring characters

ValueCountFrequency (%)
0106352
34.2%
.103652
33.3%
1100952
32.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0106352
51.3%
1100952
48.7%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0106352
34.2%
.103652
33.3%
1100952
32.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0106352
34.2%
.103652
33.3%
1100952
32.5%

static__vehicleClass_C
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
101768 
1.0
 
1884

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0101768
98.2%
1.01884
 
1.8%
2021-04-15T01:07:44.518351image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:44.576939image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0101768
98.2%
1.01884
 
1.8%

Most occurring characters

ValueCountFrequency (%)
0205420
66.1%
.103652
33.3%
11884
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0205420
99.1%
11884
 
0.9%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0205420
66.1%
.103652
33.3%
11884
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0205420
66.1%
.103652
33.3%
11884
 
0.6%

static__vehicleClass_M
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102838 
1.0
 
814

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102838
99.2%
1.0814
 
0.8%
2021-04-15T01:07:44.725211image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:44.781946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102838
99.2%
1.0814
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0206490
66.4%
.103652
33.3%
1814
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206490
99.6%
1814
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206490
66.4%
.103652
33.3%
1814
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206490
66.4%
.103652
33.3%
1814
 
0.3%

static__vehicleClass_R
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103650 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%
2021-04-15T01:07:44.931033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:44.989105image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207302
> 99.9%
12
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

index__expense_0
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103652 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103652
100.0%
2021-04-15T01:07:45.136736image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:45.192447image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103652
100.0%

Most occurring characters

ValueCountFrequency (%)
0207304
66.7%
.103652
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207304
100.0%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207304
66.7%
.103652
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207304
66.7%
.103652
33.3%

index__timesincelastevent_0
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103652 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103652
100.0%
2021-04-15T01:07:45.333595image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:45.389101image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103652
100.0%

Most occurring characters

ValueCountFrequency (%)
0207304
66.7%
.103652
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207304
100.0%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207304
66.7%
.103652
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207304
66.7%
.103652
33.3%

index__timesincecasestart_0
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103652 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103652
100.0%
2021-04-15T01:07:45.528449image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:45.586049image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103652
100.0%

Most occurring characters

ValueCountFrequency (%)
0207304
66.7%
.103652
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207304
100.0%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207304
66.7%
.103652
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207304
66.7%
.103652
33.3%

index__timesincemidnight_0
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
1320.0
76886 
1380.0
26766 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters621912
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1320.0
2nd row1380.0
3rd row1380.0
4th row1380.0
5th row1380.0
ValueCountFrequency (%)
1320.076886
74.2%
1380.026766
 
25.8%
2021-04-15T01:07:45.722379image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:45.778865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
1320.076886
74.2%
1380.026766
 
25.8%

Most occurring characters

ValueCountFrequency (%)
0207304
33.3%
1103652
16.7%
3103652
16.7%
.103652
16.7%
276886
 
12.4%
826766
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number518260
83.3%
Other Punctuation103652
 
16.7%

Most frequent character per category

ValueCountFrequency (%)
0207304
40.0%
1103652
20.0%
3103652
20.0%
276886
 
14.8%
826766
 
5.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common621912
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207304
33.3%
1103652
16.7%
3103652
16.7%
.103652
16.7%
276886
 
12.4%
826766
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII621912
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207304
33.3%
1103652
16.7%
3103652
16.7%
.103652
16.7%
276886
 
12.4%
826766
 
4.3%

index__event_nr_0
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
1.0
103652 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0
ValueCountFrequency (%)
1.0103652
100.0%
2021-04-15T01:07:45.926052image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:45.981444image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
1.0103652
100.0%

Most occurring characters

ValueCountFrequency (%)
1103652
33.3%
.103652
33.3%
0103652
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
1103652
50.0%
0103652
50.0%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
1103652
33.3%
.103652
33.3%
0103652
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
1103652
33.3%
.103652
33.3%
0103652
33.3%

index__month_0
Real number (ℝ≥0)

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.575772778
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Memory size809.9 KiB
2021-04-15T01:07:46.033324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median7
Q38
95-th percentile11
Maximum12
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.804124895
Coefficient of variation (CV)0.4264327539
Kurtosis-0.508373607
Mean6.575772778
Median Absolute Deviation (MAD)2
Skewness-0.1206890528
Sum681592
Variance7.863116425
MonotocityNot monotonic
2021-04-15T01:07:46.115239image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
717619
17.0%
817462
16.8%
613330
12.9%
59306
9.0%
36809
 
6.6%
96663
 
6.4%
46359
 
6.1%
105558
 
5.4%
25540
 
5.3%
115135
 
5.0%
Other values (2)9871
9.5%
ValueCountFrequency (%)
15034
4.9%
25540
5.3%
36809
6.6%
46359
6.1%
59306
9.0%
ValueCountFrequency (%)
124837
 
4.7%
115135
 
5.0%
105558
 
5.4%
96663
 
6.4%
817462
16.8%

index__weekday_0
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.126066067
Minimum0
Maximum6
Zeros13632
Zeros (%)13.2%
Memory size809.9 KiB
2021-04-15T01:07:46.197021image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q35
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.965176407
Coefficient of variation (CV)0.6286419943
Kurtosis-1.222108154
Mean3.126066067
Median Absolute Deviation (MAD)2
Skewness-0.1491736584
Sum324023
Variance3.86191831
MonotocityNot monotonic
2021-04-15T01:07:46.275468image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
518734
18.1%
417140
16.5%
314176
13.7%
113711
13.2%
013632
13.2%
613259
12.8%
213000
12.5%
ValueCountFrequency (%)
013632
13.2%
113711
13.2%
213000
12.5%
314176
13.7%
417140
16.5%
ValueCountFrequency (%)
613259
12.8%
518734
18.1%
417140
16.5%
314176
13.7%
213000
12.5%

index__hour_0
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
22.0
76886 
23.0
26766 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters414608
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row22.0
2nd row23.0
3rd row23.0
4th row23.0
5th row23.0
ValueCountFrequency (%)
22.076886
74.2%
23.026766
 
25.8%
2021-04-15T01:07:46.446688image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:46.503074image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
22.076886
74.2%
23.026766
 
25.8%

Most occurring characters

ValueCountFrequency (%)
2180538
43.5%
.103652
25.0%
0103652
25.0%
326766
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number310956
75.0%
Other Punctuation103652
 
25.0%

Most frequent character per category

ValueCountFrequency (%)
2180538
58.1%
0103652
33.3%
326766
 
8.6%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common414608
100.0%

Most frequent character per script

ValueCountFrequency (%)
2180538
43.5%
.103652
25.0%
0103652
25.0%
326766
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII414608
100.0%

Most frequent character per block

ValueCountFrequency (%)
2180538
43.5%
.103652
25.0%
0103652
25.0%
326766
 
6.5%

index__open_cases_0
Real number (ℝ≥0)

Distinct2746
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10161.04119
Minimum1
Maximum17269
Zeros0
Zeros (%)0.0%
Memory size809.9 KiB
2021-04-15T01:07:46.579934image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4266
Q18306
median10334
Q312219
95-th percentile15219
Maximum17269
Range17268
Interquartile range (IQR)3913

Descriptive statistics

Standard deviation3155.068253
Coefficient of variation (CV)0.3105063935
Kurtosis0.7148160023
Mean10161.04119
Median Absolute Deviation (MAD)1932
Skewness-0.4736701324
Sum1053212241
Variance9954455.678
MonotocityNot monotonic
2021-04-15T01:07:46.696388image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10074224
 
0.2%
10232221
 
0.2%
10653211
 
0.2%
7177200
 
0.2%
10641195
 
0.2%
11003182
 
0.2%
6332177
 
0.2%
14430176
 
0.2%
10455175
 
0.2%
9345171
 
0.2%
Other values (2736)101720
98.1%
ValueCountFrequency (%)
11
 
< 0.1%
54
 
< 0.1%
4238
< 0.1%
7942
< 0.1%
13759
0.1%
ValueCountFrequency (%)
1726915
< 0.1%
1726814
< 0.1%
172665
 
< 0.1%
1726417
< 0.1%
1726126
< 0.1%

index__concept:name_0_Create Fine
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
1.0
103652 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0
ValueCountFrequency (%)
1.0103652
100.0%
2021-04-15T01:07:46.891845image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:46.948334image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
1.0103652
100.0%

Most occurring characters

ValueCountFrequency (%)
1103652
33.3%
.103652
33.3%
0103652
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
1103652
50.0%
0103652
50.0%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
1103652
33.3%
.103652
33.3%
0103652
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
1103652
33.3%
.103652
33.3%
0103652
33.3%

index__org:resource_0_10.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103461 
1.0
 
191

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103461
99.8%
1.0191
 
0.2%
2021-04-15T01:07:47.088455image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:47.144917image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103461
99.8%
1.0191
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207113
66.6%
.103652
33.3%
1191
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207113
99.9%
1191
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207113
66.6%
.103652
33.3%
1191
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207113
66.6%
.103652
33.3%
1191
 
0.1%

index__org:resource_0_11.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
101724 
1.0
 
1928

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0101724
98.1%
1.01928
 
1.9%
2021-04-15T01:07:47.292862image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:47.349237image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0101724
98.1%
1.01928
 
1.9%

Most occurring characters

ValueCountFrequency (%)
0205376
66.0%
.103652
33.3%
11928
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0205376
99.1%
11928
 
0.9%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0205376
66.0%
.103652
33.3%
11928
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0205376
66.0%
.103652
33.3%
11928
 
0.6%

index__org:resource_0_12.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103495 
1.0
 
157

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103495
99.8%
1.0157
 
0.2%
2021-04-15T01:07:47.495241image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:47.551443image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103495
99.8%
1.0157
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207147
66.6%
.103652
33.3%
1157
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207147
99.9%
1157
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207147
66.6%
.103652
33.3%
1157
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207147
66.6%
.103652
33.3%
1157
 
0.1%

index__org:resource_0_14.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103647 
1.0
 
5

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103647
> 99.9%
1.05
 
< 0.1%
2021-04-15T01:07:47.700272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:47.756425image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103647
> 99.9%
1.05
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207299
66.7%
.103652
33.3%
15
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207299
> 99.9%
15
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207299
66.7%
.103652
33.3%
15
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207299
66.7%
.103652
33.3%
15
 
< 0.1%

index__org:resource_0_15.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103497 
1.0
 
155

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103497
99.9%
1.0155
 
0.1%
2021-04-15T01:07:47.902637image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:47.961119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103497
99.9%
1.0155
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207149
66.6%
.103652
33.3%
1155
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207149
99.9%
1155
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207149
66.6%
.103652
33.3%
1155
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207149
66.6%
.103652
33.3%
1155
 
< 0.1%

index__org:resource_0_16.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103290 
1.0
 
362

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103290
99.7%
1.0362
 
0.3%
2021-04-15T01:07:48.107144image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:48.163511image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103290
99.7%
1.0362
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0206942
66.6%
.103652
33.3%
1362
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206942
99.8%
1362
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206942
66.6%
.103652
33.3%
1362
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206942
66.6%
.103652
33.3%
1362
 
0.1%

index__org:resource_0_17.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103600 
1.0
 
52

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103600
99.9%
1.052
 
0.1%
2021-04-15T01:07:48.312839image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:48.369630image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103600
99.9%
1.052
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207252
66.6%
.103652
33.3%
152
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207252
> 99.9%
152
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207252
66.6%
.103652
33.3%
152
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207252
66.6%
.103652
33.3%
152
 
< 0.1%

index__org:resource_0_18.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103612 
1.0
 
40

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103612
> 99.9%
1.040
 
< 0.1%
2021-04-15T01:07:48.516297image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:48.572865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103612
> 99.9%
1.040
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207264
66.7%
.103652
33.3%
140
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207264
> 99.9%
140
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207264
66.7%
.103652
33.3%
140
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207264
66.7%
.103652
33.3%
140
 
< 0.1%

index__org:resource_0_19.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103647 
1.0
 
5

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103647
> 99.9%
1.05
 
< 0.1%
2021-04-15T01:07:48.722751image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:48.779156image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103647
> 99.9%
1.05
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207299
66.7%
.103652
33.3%
15
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207299
> 99.9%
15
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207299
66.7%
.103652
33.3%
15
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207299
66.7%
.103652
33.3%
15
 
< 0.1%

index__org:resource_0_20.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103278 
1.0
 
374

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103278
99.6%
1.0374
 
0.4%
2021-04-15T01:07:48.926660image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:48.983093image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103278
99.6%
1.0374
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206930
66.5%
.103652
33.3%
1374
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206930
99.8%
1374
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206930
66.5%
.103652
33.3%
1374
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206930
66.5%
.103652
33.3%
1374
 
0.1%

index__org:resource_0_21.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103294 
1.0
 
358

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103294
99.7%
1.0358
 
0.3%
2021-04-15T01:07:49.129462image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:49.185822image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103294
99.7%
1.0358
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0206946
66.6%
.103652
33.3%
1358
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206946
99.8%
1358
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206946
66.6%
.103652
33.3%
1358
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206946
66.6%
.103652
33.3%
1358
 
0.1%

index__org:resource_0_22.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103340 
1.0
 
312

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103340
99.7%
1.0312
 
0.3%
2021-04-15T01:07:49.333780image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:49.390113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103340
99.7%
1.0312
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0206992
66.6%
.103652
33.3%
1312
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206992
99.8%
1312
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206992
66.6%
.103652
33.3%
1312
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206992
66.6%
.103652
33.3%
1312
 
0.1%

index__org:resource_0_23.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103557 
1.0
 
95

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103557
99.9%
1.095
 
0.1%
2021-04-15T01:07:49.535844image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:49.594808image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103557
99.9%
1.095
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207209
66.6%
.103652
33.3%
195
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207209
> 99.9%
195
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207209
66.6%
.103652
33.3%
195
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207209
66.6%
.103652
33.3%
195
 
< 0.1%

index__org:resource_0_24.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103550 
1.0
 
102

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103550
99.9%
1.0102
 
0.1%
2021-04-15T01:07:49.741687image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:49.798867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103550
99.9%
1.0102
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207202
66.6%
.103652
33.3%
1102
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207202
> 99.9%
1102
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207202
66.6%
.103652
33.3%
1102
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207202
66.6%
.103652
33.3%
1102
 
< 0.1%

index__org:resource_0_25.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103247 
1.0
 
405

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103247
99.6%
1.0405
 
0.4%
2021-04-15T01:07:49.944041image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:49.998550image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103247
99.6%
1.0405
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206899
66.5%
.103652
33.3%
1405
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206899
99.8%
1405
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206899
66.5%
.103652
33.3%
1405
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206899
66.5%
.103652
33.3%
1405
 
0.1%

index__org:resource_0_26.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103003 
1.0
 
649

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103003
99.4%
1.0649
 
0.6%
2021-04-15T01:07:50.138015image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:50.191792image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103003
99.4%
1.0649
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0206655
66.5%
.103652
33.3%
1649
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206655
99.7%
1649
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206655
66.5%
.103652
33.3%
1649
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206655
66.5%
.103652
33.3%
1649
 
0.2%

index__org:resource_0_27.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103262 
1.0
 
390

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103262
99.6%
1.0390
 
0.4%
2021-04-15T01:07:50.348937image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:50.402632image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103262
99.6%
1.0390
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206914
66.5%
.103652
33.3%
1390
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206914
99.8%
1390
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206914
66.5%
.103652
33.3%
1390
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206914
66.5%
.103652
33.3%
1390
 
0.1%

index__org:resource_0_28.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
101986 
1.0
 
1666

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0101986
98.4%
1.01666
 
1.6%
2021-04-15T01:07:50.541899image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:50.597547image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0101986
98.4%
1.01666
 
1.6%

Most occurring characters

ValueCountFrequency (%)
0205638
66.1%
.103652
33.3%
11666
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0205638
99.2%
11666
 
0.8%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0205638
66.1%
.103652
33.3%
11666
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0205638
66.1%
.103652
33.3%
11666
 
0.5%

index__org:resource_0_29.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
101646 
1.0
 
2006

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0101646
98.1%
1.02006
 
1.9%
2021-04-15T01:07:50.736823image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:50.790608image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0101646
98.1%
1.02006
 
1.9%

Most occurring characters

ValueCountFrequency (%)
0205298
66.0%
.103652
33.3%
12006
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0205298
99.0%
12006
 
1.0%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0205298
66.0%
.103652
33.3%
12006
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0205298
66.0%
.103652
33.3%
12006
 
0.6%

index__org:resource_0_3.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103640 
1.0
 
12

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103640
> 99.9%
1.012
 
< 0.1%
2021-04-15T01:07:50.932801image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:50.989211image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103640
> 99.9%
1.012
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207292
66.7%
.103652
33.3%
112
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207292
> 99.9%
112
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207292
66.7%
.103652
33.3%
112
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207292
66.7%
.103652
33.3%
112
 
< 0.1%

index__org:resource_0_30.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
101969 
1.0
 
1683

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0101969
98.4%
1.01683
 
1.6%
2021-04-15T01:07:51.134851image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:51.191287image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0101969
98.4%
1.01683
 
1.6%

Most occurring characters

ValueCountFrequency (%)
0205621
66.1%
.103652
33.3%
11683
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0205621
99.2%
11683
 
0.8%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0205621
66.1%
.103652
33.3%
11683
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0205621
66.1%
.103652
33.3%
11683
 
0.5%

index__org:resource_0_31.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102642 
1.0
 
1010

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102642
99.0%
1.01010
 
1.0%
2021-04-15T01:07:51.339153image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:51.395449image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102642
99.0%
1.01010
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0206294
66.3%
.103652
33.3%
11010
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206294
99.5%
11010
 
0.5%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206294
66.3%
.103652
33.3%
11010
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206294
66.3%
.103652
33.3%
11010
 
0.3%

index__org:resource_0_32.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103282 
1.0
 
370

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103282
99.6%
1.0370
 
0.4%
2021-04-15T01:07:51.541382image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:51.599458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103282
99.6%
1.0370
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206934
66.5%
.103652
33.3%
1370
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206934
99.8%
1370
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206934
66.5%
.103652
33.3%
1370
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206934
66.5%
.103652
33.3%
1370
 
0.1%

index__org:resource_0_33.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103438 
1.0
 
214

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103438
99.8%
1.0214
 
0.2%
2021-04-15T01:07:51.745750image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:51.802063image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103438
99.8%
1.0214
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207090
66.6%
.103652
33.3%
1214
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207090
99.9%
1214
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207090
66.6%
.103652
33.3%
1214
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207090
66.6%
.103652
33.3%
1214
 
0.1%

index__org:resource_0_34.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103203 
1.0
 
449

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103203
99.6%
1.0449
 
0.4%
2021-04-15T01:07:51.948115image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:52.004427image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103203
99.6%
1.0449
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206855
66.5%
.103652
33.3%
1449
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206855
99.8%
1449
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206855
66.5%
.103652
33.3%
1449
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206855
66.5%
.103652
33.3%
1449
 
0.1%

index__org:resource_0_35.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103040 
1.0
 
612

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103040
99.4%
1.0612
 
0.6%
2021-04-15T01:07:52.150570image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:52.206869image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103040
99.4%
1.0612
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0206692
66.5%
.103652
33.3%
1612
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206692
99.7%
1612
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206692
66.5%
.103652
33.3%
1612
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206692
66.5%
.103652
33.3%
1612
 
0.2%

index__org:resource_0_36.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102880 
1.0
 
772

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102880
99.3%
1.0772
 
0.7%
2021-04-15T01:07:52.353115image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:52.409543image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102880
99.3%
1.0772
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0206532
66.4%
.103652
33.3%
1772
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206532
99.6%
1772
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206532
66.4%
.103652
33.3%
1772
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206532
66.4%
.103652
33.3%
1772
 
0.2%

index__org:resource_0_37.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103059 
1.0
 
593

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103059
99.4%
1.0593
 
0.6%
2021-04-15T01:07:52.555724image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:52.612105image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103059
99.4%
1.0593
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0206711
66.5%
.103652
33.3%
1593
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206711
99.7%
1593
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206711
66.5%
.103652
33.3%
1593
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206711
66.5%
.103652
33.3%
1593
 
0.2%

index__org:resource_0_38.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103559 
1.0
 
93

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103559
99.9%
1.093
 
0.1%
2021-04-15T01:07:52.758999image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:52.815238image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103559
99.9%
1.093
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207211
66.6%
.103652
33.3%
193
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207211
> 99.9%
193
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207211
66.6%
.103652
33.3%
193
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207211
66.6%
.103652
33.3%
193
 
< 0.1%

index__org:resource_0_39.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102950 
1.0
 
702

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102950
99.3%
1.0702
 
0.7%
2021-04-15T01:07:52.961219image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:53.017551image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102950
99.3%
1.0702
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0206602
66.4%
.103652
33.3%
1702
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206602
99.7%
1702
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206602
66.4%
.103652
33.3%
1702
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206602
66.4%
.103652
33.3%
1702
 
0.2%

index__org:resource_0_4.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103648 
1.0
 
4

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103648
> 99.9%
1.04
 
< 0.1%
2021-04-15T01:07:53.163557image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:53.219840image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103648
> 99.9%
1.04
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207300
66.7%
.103652
33.3%
14
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207300
> 99.9%
14
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207300
66.7%
.103652
33.3%
14
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207300
66.7%
.103652
33.3%
14
 
< 0.1%

index__org:resource_0_40.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
101923 
1.0
 
1729

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0101923
98.3%
1.01729
 
1.7%
2021-04-15T01:07:53.369430image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:53.427068image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0101923
98.3%
1.01729
 
1.7%

Most occurring characters

ValueCountFrequency (%)
0205575
66.1%
.103652
33.3%
11729
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0205575
99.2%
11729
 
0.8%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0205575
66.1%
.103652
33.3%
11729
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0205575
66.1%
.103652
33.3%
11729
 
0.6%

index__org:resource_0_41.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103340 
1.0
 
312

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103340
99.7%
1.0312
 
0.3%
2021-04-15T01:07:53.578334image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:53.635992image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103340
99.7%
1.0312
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0206992
66.6%
.103652
33.3%
1312
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206992
99.8%
1312
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206992
66.6%
.103652
33.3%
1312
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206992
66.6%
.103652
33.3%
1312
 
0.1%

index__org:resource_0_42.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103098 
1.0
 
554

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103098
99.5%
1.0554
 
0.5%
2021-04-15T01:07:53.784984image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:53.842613image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103098
99.5%
1.0554
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0206750
66.5%
.103652
33.3%
1554
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206750
99.7%
1554
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206750
66.5%
.103652
33.3%
1554
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206750
66.5%
.103652
33.3%
1554
 
0.2%

index__org:resource_0_43.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103444 
1.0
 
208

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103444
99.8%
1.0208
 
0.2%
2021-04-15T01:07:53.994113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:54.051622image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103444
99.8%
1.0208
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207096
66.6%
.103652
33.3%
1208
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207096
99.9%
1208
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207096
66.6%
.103652
33.3%
1208
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207096
66.6%
.103652
33.3%
1208
 
0.1%

index__org:resource_0_44.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103131 
1.0
 
521

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103131
99.5%
1.0521
 
0.5%
2021-04-15T01:07:54.200596image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:54.259500image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103131
99.5%
1.0521
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0206783
66.5%
.103652
33.3%
1521
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206783
99.7%
1521
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206783
66.5%
.103652
33.3%
1521
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206783
66.5%
.103652
33.3%
1521
 
0.2%

index__org:resource_0_45.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102779 
1.0
 
873

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102779
99.2%
1.0873
 
0.8%
2021-04-15T01:07:54.408498image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:54.466042image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102779
99.2%
1.0873
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0206431
66.4%
.103652
33.3%
1873
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206431
99.6%
1873
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206431
66.4%
.103652
33.3%
1873
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206431
66.4%
.103652
33.3%
1873
 
0.3%

index__org:resource_0_46.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103211 
1.0
 
441

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103211
99.6%
1.0441
 
0.4%
2021-04-15T01:07:54.616071image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:54.673671image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103211
99.6%
1.0441
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206863
66.5%
.103652
33.3%
1441
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206863
99.8%
1441
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206863
66.5%
.103652
33.3%
1441
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206863
66.5%
.103652
33.3%
1441
 
0.1%

index__org:resource_0_47.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103420 
1.0
 
232

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103420
99.8%
1.0232
 
0.2%
2021-04-15T01:07:54.822590image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:54.880327image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103420
99.8%
1.0232
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207072
66.6%
.103652
33.3%
1232
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207072
99.9%
1232
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207072
66.6%
.103652
33.3%
1232
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207072
66.6%
.103652
33.3%
1232
 
0.1%

index__org:resource_0_48.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103261 
1.0
 
391

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103261
99.6%
1.0391
 
0.4%
2021-04-15T01:07:55.028898image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:55.085071image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103261
99.6%
1.0391
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206913
66.5%
.103652
33.3%
1391
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206913
99.8%
1391
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206913
66.5%
.103652
33.3%
1391
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206913
66.5%
.103652
33.3%
1391
 
0.1%

index__org:resource_0_49.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
101287 
1.0
 
2365

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0101287
97.7%
1.02365
 
2.3%
2021-04-15T01:07:55.232319image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:55.288091image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0101287
97.7%
1.02365
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0204939
65.9%
.103652
33.3%
12365
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0204939
98.9%
12365
 
1.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0204939
65.9%
.103652
33.3%
12365
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0204939
65.9%
.103652
33.3%
12365
 
0.8%

index__org:resource_0_50.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102740 
1.0
 
912

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102740
99.1%
1.0912
 
0.9%
2021-04-15T01:07:55.427199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:55.481097image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102740
99.1%
1.0912
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0206392
66.4%
.103652
33.3%
1912
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206392
99.6%
1912
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206392
66.4%
.103652
33.3%
1912
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206392
66.4%
.103652
33.3%
1912
 
0.3%

index__org:resource_0_51.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103586 
1.0
 
66

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103586
99.9%
1.066
 
0.1%
2021-04-15T01:07:55.622302image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:55.676054image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103586
99.9%
1.066
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207238
66.6%
.103652
33.3%
166
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207238
> 99.9%
166
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207238
66.6%
.103652
33.3%
166
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207238
66.6%
.103652
33.3%
166
 
< 0.1%

index__org:resource_0_52.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103285 
1.0
 
367

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103285
99.6%
1.0367
 
0.4%
2021-04-15T01:07:55.816260image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:55.870167image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103285
99.6%
1.0367
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206937
66.5%
.103652
33.3%
1367
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206937
99.8%
1367
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206937
66.5%
.103652
33.3%
1367
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206937
66.5%
.103652
33.3%
1367
 
0.1%

index__org:resource_0_53.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
101906 
1.0
 
1746

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0101906
98.3%
1.01746
 
1.7%
2021-04-15T01:07:56.012032image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:56.066554image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0101906
98.3%
1.01746
 
1.7%

Most occurring characters

ValueCountFrequency (%)
0205558
66.1%
.103652
33.3%
11746
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0205558
99.2%
11746
 
0.8%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0205558
66.1%
.103652
33.3%
11746
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0205558
66.1%
.103652
33.3%
11746
 
0.6%

index__org:resource_0_536.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
99666 
1.0
 
3986

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.099666
96.2%
1.03986
 
3.8%
2021-04-15T01:07:56.205592image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:56.261398image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.099666
96.2%
1.03986
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0203318
65.4%
.103652
33.3%
13986
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0203318
98.1%
13986
 
1.9%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0203318
65.4%
.103652
33.3%
13986
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0203318
65.4%
.103652
33.3%
13986
 
1.3%

index__org:resource_0_537.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
97986 
1.0
 
5666

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row1.0
4th row1.0
5th row1.0
ValueCountFrequency (%)
0.097986
94.5%
1.05666
 
5.5%
2021-04-15T01:07:56.397385image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:56.451055image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.097986
94.5%
1.05666
 
5.5%

Most occurring characters

ValueCountFrequency (%)
0201638
64.8%
.103652
33.3%
15666
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0201638
97.3%
15666
 
2.7%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0201638
64.8%
.103652
33.3%
15666
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0201638
64.8%
.103652
33.3%
15666
 
1.8%

index__org:resource_0_538.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
96797 
1.0
 
6855

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.096797
93.4%
1.06855
 
6.6%
2021-04-15T01:07:56.586907image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:56.640683image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.096797
93.4%
1.06855
 
6.6%

Most occurring characters

ValueCountFrequency (%)
0200449
64.5%
.103652
33.3%
16855
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0200449
96.7%
16855
 
3.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0200449
64.5%
.103652
33.3%
16855
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0200449
64.5%
.103652
33.3%
16855
 
2.2%

index__org:resource_0_54.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103482 
1.0
 
170

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103482
99.8%
1.0170
 
0.2%
2021-04-15T01:07:56.779750image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:56.833391image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103482
99.8%
1.0170
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207134
66.6%
.103652
33.3%
1170
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207134
99.9%
1170
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207134
66.6%
.103652
33.3%
1170
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207134
66.6%
.103652
33.3%
1170
 
0.1%

index__org:resource_0_540.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103108 
1.0
 
544

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103108
99.5%
1.0544
 
0.5%
2021-04-15T01:07:56.972854image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:57.026480image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103108
99.5%
1.0544
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0206760
66.5%
.103652
33.3%
1544
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206760
99.7%
1544
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206760
66.5%
.103652
33.3%
1544
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206760
66.5%
.103652
33.3%
1544
 
0.2%

index__org:resource_0_541.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
97588 
1.0
 
6064

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.097588
94.1%
1.06064
 
5.9%
2021-04-15T01:07:57.162441image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:57.216104image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.097588
94.1%
1.06064
 
5.9%

Most occurring characters

ValueCountFrequency (%)
0201240
64.7%
.103652
33.3%
16064
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0201240
97.1%
16064
 
2.9%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0201240
64.7%
.103652
33.3%
16064
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0201240
64.7%
.103652
33.3%
16064
 
2.0%

index__org:resource_0_546.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102101 
1.0
 
1551

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102101
98.5%
1.01551
 
1.5%
2021-04-15T01:07:57.355226image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:57.409061image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102101
98.5%
1.01551
 
1.5%

Most occurring characters

ValueCountFrequency (%)
0205753
66.2%
.103652
33.3%
11551
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0205753
99.3%
11551
 
0.7%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0205753
66.2%
.103652
33.3%
11551
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0205753
66.2%
.103652
33.3%
11551
 
0.5%

index__org:resource_0_548.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102024 
1.0
 
1628

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102024
98.4%
1.01628
 
1.6%
2021-04-15T01:07:57.548324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:57.602093image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102024
98.4%
1.01628
 
1.6%

Most occurring characters

ValueCountFrequency (%)
0205676
66.1%
.103652
33.3%
11628
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0205676
99.2%
11628
 
0.8%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0205676
66.1%
.103652
33.3%
11628
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0205676
66.1%
.103652
33.3%
11628
 
0.5%

index__org:resource_0_55.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103488 
1.0
 
164

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103488
99.8%
1.0164
 
0.2%
2021-04-15T01:07:57.741954image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:57.795615image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103488
99.8%
1.0164
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207140
66.6%
.103652
33.3%
1164
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207140
99.9%
1164
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207140
66.6%
.103652
33.3%
1164
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207140
66.6%
.103652
33.3%
1164
 
0.1%

index__org:resource_0_550.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
96971 
1.0
 
6681

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.096971
93.6%
1.06681
 
6.4%
2021-04-15T01:07:57.931673image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:57.985491image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.096971
93.6%
1.06681
 
6.4%

Most occurring characters

ValueCountFrequency (%)
0200623
64.5%
.103652
33.3%
16681
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0200623
96.8%
16681
 
3.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0200623
64.5%
.103652
33.3%
16681
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0200623
64.5%
.103652
33.3%
16681
 
2.1%

index__org:resource_0_551.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103637 
1.0
 
15

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103637
> 99.9%
1.015
 
< 0.1%
2021-04-15T01:07:58.124656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:58.178364image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103637
> 99.9%
1.015
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207289
66.7%
.103652
33.3%
115
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207289
> 99.9%
115
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207289
66.7%
.103652
33.3%
115
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207289
66.7%
.103652
33.3%
115
 
< 0.1%

index__org:resource_0_552.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102755 
1.0
 
897

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102755
99.1%
1.0897
 
0.9%
2021-04-15T01:07:58.318285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:58.371932image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102755
99.1%
1.0897
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0206407
66.4%
.103652
33.3%
1897
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206407
99.6%
1897
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206407
66.4%
.103652
33.3%
1897
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206407
66.4%
.103652
33.3%
1897
 
0.3%

index__org:resource_0_553.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103489 
1.0
 
163

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103489
99.8%
1.0163
 
0.2%
2021-04-15T01:07:58.511015image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:58.566344image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103489
99.8%
1.0163
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207141
66.6%
.103652
33.3%
1163
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207141
99.9%
1163
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207141
66.6%
.103652
33.3%
1163
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207141
66.6%
.103652
33.3%
1163
 
0.1%

index__org:resource_0_554.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103377 
1.0
 
275

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103377
99.7%
1.0275
 
0.3%
2021-04-15T01:07:58.705827image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:58.759435image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103377
99.7%
1.0275
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0207029
66.6%
.103652
33.3%
1275
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207029
99.9%
1275
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207029
66.6%
.103652
33.3%
1275
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207029
66.6%
.103652
33.3%
1275
 
0.1%

index__org:resource_0_555.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102768 
1.0
 
884

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102768
99.1%
1.0884
 
0.9%
2021-04-15T01:07:58.898380image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:58.954185image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102768
99.1%
1.0884
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0206420
66.4%
.103652
33.3%
1884
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206420
99.6%
1884
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206420
66.4%
.103652
33.3%
1884
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206420
66.4%
.103652
33.3%
1884
 
0.3%

index__org:resource_0_556.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102784 
1.0
 
868

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102784
99.2%
1.0868
 
0.8%
2021-04-15T01:07:59.099959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:59.156056image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102784
99.2%
1.0868
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0206436
66.4%
.103652
33.3%
1868
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206436
99.6%
1868
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206436
66.4%
.103652
33.3%
1868
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206436
66.4%
.103652
33.3%
1868
 
0.3%

index__org:resource_0_557.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
99496 
1.0
 
4156

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.099496
96.0%
1.04156
 
4.0%
2021-04-15T01:07:59.301733image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:59.357963image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.099496
96.0%
1.04156
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0203148
65.3%
.103652
33.3%
14156
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0203148
98.0%
14156
 
2.0%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0203148
65.3%
.103652
33.3%
14156
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0203148
65.3%
.103652
33.3%
14156
 
1.3%

index__org:resource_0_558.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
100516 
1.0
 
3136

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0100516
97.0%
1.03136
 
3.0%
2021-04-15T01:07:59.503374image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:59.559528image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0100516
97.0%
1.03136
 
3.0%

Most occurring characters

ValueCountFrequency (%)
0204168
65.7%
.103652
33.3%
13136
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0204168
98.5%
13136
 
1.5%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0204168
65.7%
.103652
33.3%
13136
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0204168
65.7%
.103652
33.3%
13136
 
1.0%

index__org:resource_0_559.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
99080 
1.0
 
4572

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.099080
95.6%
1.04572
 
4.4%
2021-04-15T01:07:59.705229image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:59.761454image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.099080
95.6%
1.04572
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0202732
65.2%
.103652
33.3%
14572
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0202732
97.8%
14572
 
2.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0202732
65.2%
.103652
33.3%
14572
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0202732
65.2%
.103652
33.3%
14572
 
1.5%

index__org:resource_0_56.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102976 
1.0
 
676

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102976
99.3%
1.0676
 
0.7%
2021-04-15T01:07:59.908483image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:07:59.964739image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102976
99.3%
1.0676
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0206628
66.4%
.103652
33.3%
1676
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206628
99.7%
1676
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206628
66.4%
.103652
33.3%
1676
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206628
66.4%
.103652
33.3%
1676
 
0.2%

index__org:resource_0_560.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102322 
1.0
 
1330

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102322
98.7%
1.01330
 
1.3%
2021-04-15T01:08:00.110420image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:00.166575image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102322
98.7%
1.01330
 
1.3%

Most occurring characters

ValueCountFrequency (%)
0205974
66.2%
.103652
33.3%
11330
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0205974
99.4%
11330
 
0.6%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0205974
66.2%
.103652
33.3%
11330
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0205974
66.2%
.103652
33.3%
11330
 
0.4%

index__org:resource_0_561.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
100643 
1.0
 
3009

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0100643
97.1%
1.03009
 
2.9%
2021-04-15T01:08:00.313370image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:00.369727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0100643
97.1%
1.03009
 
2.9%

Most occurring characters

ValueCountFrequency (%)
0204295
65.7%
.103652
33.3%
13009
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0204295
98.5%
13009
 
1.5%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0204295
65.7%
.103652
33.3%
13009
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0204295
65.7%
.103652
33.3%
13009
 
1.0%

index__org:resource_0_562.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102726 
1.0
 
926

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102726
99.1%
1.0926
 
0.9%
2021-04-15T01:08:00.527987image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:00.585312image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102726
99.1%
1.0926
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0206378
66.4%
.103652
33.3%
1926
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206378
99.6%
1926
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206378
66.4%
.103652
33.3%
1926
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206378
66.4%
.103652
33.3%
1926
 
0.3%

index__org:resource_0_563.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102628 
1.0
 
1024

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102628
99.0%
1.01024
 
1.0%
2021-04-15T01:08:00.731033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:00.787048image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102628
99.0%
1.01024
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0206280
66.3%
.103652
33.3%
11024
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206280
99.5%
11024
 
0.5%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206280
66.3%
.103652
33.3%
11024
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206280
66.3%
.103652
33.3%
11024
 
0.3%

index__org:resource_0_564.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102801 
1.0
 
851

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102801
99.2%
1.0851
 
0.8%
2021-04-15T01:08:00.933630image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:00.989782image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102801
99.2%
1.0851
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0206453
66.4%
.103652
33.3%
1851
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206453
99.6%
1851
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206453
66.4%
.103652
33.3%
1851
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206453
66.4%
.103652
33.3%
1851
 
0.3%

index__org:resource_0_565.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103066 
1.0
 
586

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103066
99.4%
1.0586
 
0.6%
2021-04-15T01:08:01.135395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:01.192397image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103066
99.4%
1.0586
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0206718
66.5%
.103652
33.3%
1586
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206718
99.7%
1586
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206718
66.5%
.103652
33.3%
1586
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206718
66.5%
.103652
33.3%
1586
 
0.2%

index__org:resource_0_566.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103321 
1.0
 
331

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103321
99.7%
1.0331
 
0.3%
2021-04-15T01:08:01.338145image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:01.394582image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103321
99.7%
1.0331
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0206973
66.6%
.103652
33.3%
1331
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206973
99.8%
1331
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206973
66.6%
.103652
33.3%
1331
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206973
66.6%
.103652
33.3%
1331
 
0.1%

index__org:resource_0_567.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103583 
1.0
 
69

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103583
99.9%
1.069
 
0.1%
2021-04-15T01:08:01.540655image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:01.596796image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103583
99.9%
1.069
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207235
66.6%
.103652
33.3%
169
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207235
> 99.9%
169
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207235
66.6%
.103652
33.3%
169
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207235
66.6%
.103652
33.3%
169
 
< 0.1%

index__org:resource_0_568.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103575 
1.0
 
77

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103575
99.9%
1.077
 
0.1%
2021-04-15T01:08:01.742745image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:01.798874image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103575
99.9%
1.077
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207227
66.6%
.103652
33.3%
177
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207227
> 99.9%
177
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207227
66.6%
.103652
33.3%
177
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207227
66.6%
.103652
33.3%
177
 
< 0.1%

index__org:resource_0_57.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102852 
1.0
 
800

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102852
99.2%
1.0800
 
0.8%
2021-04-15T01:08:01.945144image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:02.001445image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102852
99.2%
1.0800
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0206504
66.4%
.103652
33.3%
1800
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206504
99.6%
1800
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206504
66.4%
.103652
33.3%
1800
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206504
66.4%
.103652
33.3%
1800
 
0.3%

index__org:resource_0_58.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103237 
1.0
 
415

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103237
99.6%
1.0415
 
0.4%
2021-04-15T01:08:02.147342image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:02.203498image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103237
99.6%
1.0415
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206889
66.5%
.103652
33.3%
1415
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206889
99.8%
1415
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206889
66.5%
.103652
33.3%
1415
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206889
66.5%
.103652
33.3%
1415
 
0.1%

index__org:resource_0_59.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103604 
1.0
 
48

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103604
> 99.9%
1.048
 
< 0.1%
2021-04-15T01:08:02.349213image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:02.405394image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103604
> 99.9%
1.048
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207256
66.7%
.103652
33.3%
148
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207256
> 99.9%
148
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207256
66.7%
.103652
33.3%
148
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207256
66.7%
.103652
33.3%
148
 
< 0.1%

index__org:resource_0_60.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103640 
1.0
 
12

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103640
> 99.9%
1.012
 
< 0.1%
2021-04-15T01:08:02.550775image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:02.607073image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103640
> 99.9%
1.012
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207292
66.7%
.103652
33.3%
112
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207292
> 99.9%
112
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207292
66.7%
.103652
33.3%
112
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207292
66.7%
.103652
33.3%
112
 
< 0.1%

index__org:resource_0_704.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102902 
1.0
 
750

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102902
99.3%
1.0750
 
0.7%
2021-04-15T01:08:02.752548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:02.808624image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102902
99.3%
1.0750
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0206554
66.4%
.103652
33.3%
1750
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206554
99.6%
1750
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206554
66.4%
.103652
33.3%
1750
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206554
66.4%
.103652
33.3%
1750
 
0.2%

index__org:resource_0_8.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103631 
1.0
 
21

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103631
> 99.9%
1.021
 
< 0.1%
2021-04-15T01:08:02.954431image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:03.010761image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103631
> 99.9%
1.021
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207283
66.7%
.103652
33.3%
121
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207283
> 99.9%
121
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207283
66.7%
.103652
33.3%
121
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207283
66.7%
.103652
33.3%
121
 
< 0.1%

index__org:resource_0_802.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102994 
1.0
 
658

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102994
99.4%
1.0658
 
0.6%
2021-04-15T01:08:03.156452image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:03.212859image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102994
99.4%
1.0658
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0206646
66.5%
.103652
33.3%
1658
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206646
99.7%
1658
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206646
66.5%
.103652
33.3%
1658
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206646
66.5%
.103652
33.3%
1658
 
0.2%

index__org:resource_0_807.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103402 
1.0
 
250

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103402
99.8%
1.0250
 
0.2%
2021-04-15T01:08:03.358916image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:03.415184image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103402
99.8%
1.0250
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207054
66.6%
.103652
33.3%
1250
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207054
99.9%
1250
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207054
66.6%
.103652
33.3%
1250
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207054
66.6%
.103652
33.3%
1250
 
0.1%

index__org:resource_0_808.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103432 
1.0
 
220

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103432
99.8%
1.0220
 
0.2%
2021-04-15T01:08:03.560588image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:03.616820image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103432
99.8%
1.0220
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207084
66.6%
.103652
33.3%
1220
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207084
99.9%
1220
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207084
66.6%
.103652
33.3%
1220
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207084
66.6%
.103652
33.3%
1220
 
0.1%

index__org:resource_0_810.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103049 
1.0
 
603

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103049
99.4%
1.0603
 
0.6%
2021-04-15T01:08:03.763350image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:03.819578image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103049
99.4%
1.0603
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0206701
66.5%
.103652
33.3%
1603
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206701
99.7%
1603
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206701
66.5%
.103652
33.3%
1603
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206701
66.5%
.103652
33.3%
1603
 
0.2%

index__org:resource_0_811.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103447 
1.0
 
205

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103447
99.8%
1.0205
 
0.2%
2021-04-15T01:08:03.965509image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:04.022183image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103447
99.8%
1.0205
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207099
66.6%
.103652
33.3%
1205
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207099
99.9%
1205
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207099
66.6%
.103652
33.3%
1205
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207099
66.6%
.103652
33.3%
1205
 
0.1%

index__org:resource_0_813.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103461 
1.0
 
191

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103461
99.8%
1.0191
 
0.2%
2021-04-15T01:08:04.168407image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:04.224629image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103461
99.8%
1.0191
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207113
66.6%
.103652
33.3%
1191
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207113
99.9%
1191
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207113
66.6%
.103652
33.3%
1191
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207113
66.6%
.103652
33.3%
1191
 
0.1%

index__org:resource_0_816.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103217 
1.0
 
435

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103217
99.6%
1.0435
 
0.4%
2021-04-15T01:08:04.370833image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:04.427295image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103217
99.6%
1.0435
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206869
66.5%
.103652
33.3%
1435
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206869
99.8%
1435
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206869
66.5%
.103652
33.3%
1435
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206869
66.5%
.103652
33.3%
1435
 
0.1%

index__org:resource_0_817.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103329 
1.0
 
323

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103329
99.7%
1.0323
 
0.3%
2021-04-15T01:08:04.573259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:04.629707image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103329
99.7%
1.0323
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0206981
66.6%
.103652
33.3%
1323
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206981
99.8%
1323
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206981
66.6%
.103652
33.3%
1323
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206981
66.6%
.103652
33.3%
1323
 
0.1%

index__org:resource_0_818.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103481 
1.0
 
171

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103481
99.8%
1.0171
 
0.2%
2021-04-15T01:08:04.775120image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:04.833622image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103481
99.8%
1.0171
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207133
66.6%
.103652
33.3%
1171
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207133
99.9%
1171
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207133
66.6%
.103652
33.3%
1171
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207133
66.6%
.103652
33.3%
1171
 
0.1%

index__org:resource_0_819.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103314 
1.0
 
338

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103314
99.7%
1.0338
 
0.3%
2021-04-15T01:08:04.979225image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:05.035442image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103314
99.7%
1.0338
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0206966
66.6%
.103652
33.3%
1338
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206966
99.8%
1338
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206966
66.6%
.103652
33.3%
1338
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206966
66.6%
.103652
33.3%
1338
 
0.1%

index__org:resource_0_820.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102527 
1.0
 
1125

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102527
98.9%
1.01125
 
1.1%
2021-04-15T01:08:05.181479image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:05.237705image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102527
98.9%
1.01125
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0206179
66.3%
.103652
33.3%
11125
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206179
99.5%
11125
 
0.5%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206179
66.3%
.103652
33.3%
11125
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206179
66.3%
.103652
33.3%
11125
 
0.4%

index__org:resource_0_821.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103051 
1.0
 
601

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103051
99.4%
1.0601
 
0.6%
2021-04-15T01:08:05.383924image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:05.440331image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103051
99.4%
1.0601
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0206703
66.5%
.103652
33.3%
1601
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206703
99.7%
1601
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206703
66.5%
.103652
33.3%
1601
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206703
66.5%
.103652
33.3%
1601
 
0.2%

index__org:resource_0_823.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102946 
1.0
 
706

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102946
99.3%
1.0706
 
0.7%
2021-04-15T01:08:05.585978image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:05.642170image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102946
99.3%
1.0706
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0206598
66.4%
.103652
33.3%
1706
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206598
99.7%
1706
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206598
66.4%
.103652
33.3%
1706
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206598
66.4%
.103652
33.3%
1706
 
0.2%

index__org:resource_0_824.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102769 
1.0
 
883

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102769
99.1%
1.0883
 
0.9%
2021-04-15T01:08:05.788273image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:05.844522image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102769
99.1%
1.0883
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0206421
66.4%
.103652
33.3%
1883
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206421
99.6%
1883
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206421
66.4%
.103652
33.3%
1883
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206421
66.4%
.103652
33.3%
1883
 
0.3%

index__org:resource_0_825.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102922 
1.0
 
730

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102922
99.3%
1.0730
 
0.7%
2021-04-15T01:08:05.992585image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:06.048740image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102922
99.3%
1.0730
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0206574
66.4%
.103652
33.3%
1730
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206574
99.6%
1730
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206574
66.4%
.103652
33.3%
1730
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206574
66.4%
.103652
33.3%
1730
 
0.2%

index__org:resource_0_826.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103356 
1.0
 
296

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103356
99.7%
1.0296
 
0.3%
2021-04-15T01:08:06.196797image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:06.252936image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103356
99.7%
1.0296
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0207008
66.6%
.103652
33.3%
1296
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207008
99.9%
1296
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207008
66.6%
.103652
33.3%
1296
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207008
66.6%
.103652
33.3%
1296
 
0.1%

index__org:resource_0_827.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103050 
1.0
 
602

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103050
99.4%
1.0602
 
0.6%
2021-04-15T01:08:06.398324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:06.456869image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103050
99.4%
1.0602
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0206702
66.5%
.103652
33.3%
1602
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206702
99.7%
1602
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206702
66.5%
.103652
33.3%
1602
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206702
66.5%
.103652
33.3%
1602
 
0.2%

index__org:resource_0_828.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102997 
1.0
 
655

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102997
99.4%
1.0655
 
0.6%
2021-04-15T01:08:06.602683image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:06.658939image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102997
99.4%
1.0655
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0206649
66.5%
.103652
33.3%
1655
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206649
99.7%
1655
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206649
66.5%
.103652
33.3%
1655
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206649
66.5%
.103652
33.3%
1655
 
0.2%

index__org:resource_0_829.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102855 
1.0
 
797

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102855
99.2%
1.0797
 
0.8%
2021-04-15T01:08:06.806904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:06.863113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102855
99.2%
1.0797
 
0.8%

Most occurring characters

ValueCountFrequency (%)
0206507
66.4%
.103652
33.3%
1797
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206507
99.6%
1797
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206507
66.4%
.103652
33.3%
1797
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206507
66.4%
.103652
33.3%
1797
 
0.3%

index__org:resource_0_830.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103363 
1.0
 
289

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103363
99.7%
1.0289
 
0.3%
2021-04-15T01:08:07.008836image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:07.065099image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103363
99.7%
1.0289
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0207015
66.6%
.103652
33.3%
1289
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207015
99.9%
1289
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207015
66.6%
.103652
33.3%
1289
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207015
66.6%
.103652
33.3%
1289
 
0.1%

index__org:resource_0_831.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102739 
1.0
 
913

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102739
99.1%
1.0913
 
0.9%
2021-04-15T01:08:07.213296image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:07.269562image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102739
99.1%
1.0913
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0206391
66.4%
.103652
33.3%
1913
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206391
99.6%
1913
 
0.4%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206391
66.4%
.103652
33.3%
1913
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206391
66.4%
.103652
33.3%
1913
 
0.3%

index__org:resource_0_832.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103304 
1.0
 
348

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103304
99.7%
1.0348
 
0.3%
2021-04-15T01:08:07.415465image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:07.474330image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103304
99.7%
1.0348
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0206956
66.6%
.103652
33.3%
1348
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206956
99.8%
1348
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206956
66.6%
.103652
33.3%
1348
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206956
66.6%
.103652
33.3%
1348
 
0.1%

index__org:resource_0_833.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103196 
1.0
 
456

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103196
99.6%
1.0456
 
0.4%
2021-04-15T01:08:07.619569image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:07.675656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103196
99.6%
1.0456
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206848
66.5%
.103652
33.3%
1456
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206848
99.8%
1456
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206848
66.5%
.103652
33.3%
1456
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206848
66.5%
.103652
33.3%
1456
 
0.1%

index__org:resource_0_834.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103287 
1.0
 
365

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103287
99.6%
1.0365
 
0.4%
2021-04-15T01:08:07.824526image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:07.880841image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103287
99.6%
1.0365
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206939
66.5%
.103652
33.3%
1365
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206939
99.8%
1365
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206939
66.5%
.103652
33.3%
1365
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206939
66.5%
.103652
33.3%
1365
 
0.1%

index__org:resource_0_835.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103466 
1.0
 
186

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103466
99.8%
1.0186
 
0.2%
2021-04-15T01:08:08.026832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:08.083231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103466
99.8%
1.0186
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207118
66.6%
.103652
33.3%
1186
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207118
99.9%
1186
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207118
66.6%
.103652
33.3%
1186
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207118
66.6%
.103652
33.3%
1186
 
0.1%

index__org:resource_0_836.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103216 
1.0
 
436

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103216
99.6%
1.0436
 
0.4%
2021-04-15T01:08:08.231748image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:08.288029image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103216
99.6%
1.0436
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206868
66.5%
.103652
33.3%
1436
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206868
99.8%
1436
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206868
66.5%
.103652
33.3%
1436
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206868
66.5%
.103652
33.3%
1436
 
0.1%

index__org:resource_0_837.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103361 
1.0
 
291

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103361
99.7%
1.0291
 
0.3%
2021-04-15T01:08:08.434197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:08.493308image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103361
99.7%
1.0291
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0207013
66.6%
.103652
33.3%
1291
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207013
99.9%
1291
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207013
66.6%
.103652
33.3%
1291
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207013
66.6%
.103652
33.3%
1291
 
0.1%

index__org:resource_0_838.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103233 
1.0
 
419

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103233
99.6%
1.0419
 
0.4%
2021-04-15T01:08:08.639514image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:08.696233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103233
99.6%
1.0419
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206885
66.5%
.103652
33.3%
1419
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206885
99.8%
1419
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206885
66.5%
.103652
33.3%
1419
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206885
66.5%
.103652
33.3%
1419
 
0.1%

index__org:resource_0_839.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102987 
1.0
 
665

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102987
99.4%
1.0665
 
0.6%
2021-04-15T01:08:08.841842image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:08.898012image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102987
99.4%
1.0665
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0206639
66.5%
.103652
33.3%
1665
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206639
99.7%
1665
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206639
66.5%
.103652
33.3%
1665
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206639
66.5%
.103652
33.3%
1665
 
0.2%

index__org:resource_0_840.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103168 
1.0
 
484

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103168
99.5%
1.0484
 
0.5%
2021-04-15T01:08:09.044099image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:09.100453image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103168
99.5%
1.0484
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0206820
66.5%
.103652
33.3%
1484
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206820
99.8%
1484
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206820
66.5%
.103652
33.3%
1484
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206820
66.5%
.103652
33.3%
1484
 
0.2%

index__org:resource_0_841.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103363 
1.0
 
289

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103363
99.7%
1.0289
 
0.3%
2021-04-15T01:08:09.246517image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:09.302701image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103363
99.7%
1.0289
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0207015
66.6%
.103652
33.3%
1289
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207015
99.9%
1289
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207015
66.6%
.103652
33.3%
1289
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207015
66.6%
.103652
33.3%
1289
 
0.1%

index__org:resource_0_842.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103281 
1.0
 
371

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103281
99.6%
1.0371
 
0.4%
2021-04-15T01:08:09.448174image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:09.504350image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103281
99.6%
1.0371
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0206933
66.5%
.103652
33.3%
1371
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206933
99.8%
1371
 
0.2%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206933
66.5%
.103652
33.3%
1371
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206933
66.5%
.103652
33.3%
1371
 
0.1%

index__org:resource_0_843.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103393 
1.0
 
259

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103393
99.8%
1.0259
 
0.2%
2021-04-15T01:08:09.649789image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:09.706023image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103393
99.8%
1.0259
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207045
66.6%
.103652
33.3%
1259
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207045
99.9%
1259
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207045
66.6%
.103652
33.3%
1259
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207045
66.6%
.103652
33.3%
1259
 
0.1%

index__org:resource_0_844.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103398 
1.0
 
254

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103398
99.8%
1.0254
 
0.2%
2021-04-15T01:08:09.852883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:09.909038image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103398
99.8%
1.0254
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207050
66.6%
.103652
33.3%
1254
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207050
99.9%
1254
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207050
66.6%
.103652
33.3%
1254
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207050
66.6%
.103652
33.3%
1254
 
0.1%

index__org:resource_0_845.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103427 
1.0
 
225

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103427
99.8%
1.0225
 
0.2%
2021-04-15T01:08:10.054532image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:10.110739image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103427
99.8%
1.0225
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207079
66.6%
.103652
33.3%
1225
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207079
99.9%
1225
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207079
66.6%
.103652
33.3%
1225
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207079
66.6%
.103652
33.3%
1225
 
0.1%

index__org:resource_0_846.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103601 
1.0
 
51

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103601
> 99.9%
1.051
 
< 0.1%
2021-04-15T01:08:10.256483image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:10.312844image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103601
> 99.9%
1.051
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207253
66.7%
.103652
33.3%
151
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207253
> 99.9%
151
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207253
66.7%
.103652
33.3%
151
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207253
66.7%
.103652
33.3%
151
 
< 0.1%

index__org:resource_0_847.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103544 
1.0
 
108

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103544
99.9%
1.0108
 
0.1%
2021-04-15T01:08:10.462857image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:10.519004image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103544
99.9%
1.0108
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207196
66.6%
.103652
33.3%
1108
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207196
99.9%
1108
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207196
66.6%
.103652
33.3%
1108
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207196
66.6%
.103652
33.3%
1108
 
< 0.1%

index__org:resource_0_848.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103542 
1.0
 
110

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103542
99.9%
1.0110
 
0.1%
2021-04-15T01:08:10.664536image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:10.720696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103542
99.9%
1.0110
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207194
66.6%
.103652
33.3%
1110
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207194
99.9%
1110
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207194
66.6%
.103652
33.3%
1110
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207194
66.6%
.103652
33.3%
1110
 
< 0.1%

index__org:resource_0_849.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103585 
1.0
 
67

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103585
99.9%
1.067
 
0.1%
2021-04-15T01:08:10.876146image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:10.932709image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103585
99.9%
1.067
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207237
66.6%
.103652
33.3%
167
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207237
> 99.9%
167
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207237
66.6%
.103652
33.3%
167
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207237
66.6%
.103652
33.3%
167
 
< 0.1%

index__org:resource_0_850.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103415 
1.0
 
237

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103415
99.8%
1.0237
 
0.2%
2021-04-15T01:08:11.080343image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:11.136611image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103415
99.8%
1.0237
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207067
66.6%
.103652
33.3%
1237
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207067
99.9%
1237
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207067
66.6%
.103652
33.3%
1237
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207067
66.6%
.103652
33.3%
1237
 
0.1%

index__org:resource_0_851.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103558 
1.0
 
94

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103558
99.9%
1.094
 
0.1%
2021-04-15T01:08:11.282221image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:11.338513image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103558
99.9%
1.094
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207210
66.6%
.103652
33.3%
194
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207210
> 99.9%
194
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207210
66.6%
.103652
33.3%
194
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207210
66.6%
.103652
33.3%
194
 
< 0.1%

index__org:resource_0_852.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103487 
1.0
 
165

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103487
99.8%
1.0165
 
0.2%
2021-04-15T01:08:11.486387image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:11.542446image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103487
99.8%
1.0165
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0207139
66.6%
.103652
33.3%
1165
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207139
99.9%
1165
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207139
66.6%
.103652
33.3%
1165
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207139
66.6%
.103652
33.3%
1165
 
0.1%

index__org:resource_0_853.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103594 
1.0
 
58

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103594
99.9%
1.058
 
0.1%
2021-04-15T01:08:11.688037image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:11.748909image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103594
99.9%
1.058
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207246
66.6%
.103652
33.3%
158
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207246
> 99.9%
158
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207246
66.6%
.103652
33.3%
158
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207246
66.6%
.103652
33.3%
158
 
< 0.1%

index__org:resource_0_854.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103596 
1.0
 
56

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103596
99.9%
1.056
 
0.1%
2021-04-15T01:08:11.894444image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:11.950627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103596
99.9%
1.056
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207248
66.6%
.103652
33.3%
156
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207248
> 99.9%
156
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207248
66.6%
.103652
33.3%
156
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207248
66.6%
.103652
33.3%
156
 
< 0.1%

index__org:resource_0_855.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103540 
1.0
 
112

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103540
99.9%
1.0112
 
0.1%
2021-04-15T01:08:12.095780image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:12.151870image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103540
99.9%
1.0112
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207192
66.6%
.103652
33.3%
1112
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207192
99.9%
1112
 
0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207192
66.6%
.103652
33.3%
1112
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207192
66.6%
.103652
33.3%
1112
 
< 0.1%

index__org:resource_0_856.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103565 
1.0
 
87

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103565
99.9%
1.087
 
0.1%
2021-04-15T01:08:12.297363image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:12.353882image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103565
99.9%
1.087
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207217
66.6%
.103652
33.3%
187
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207217
> 99.9%
187
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207217
66.6%
.103652
33.3%
187
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207217
66.6%
.103652
33.3%
187
 
< 0.1%

index__org:resource_0_857.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103588 
1.0
 
64

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103588
99.9%
1.064
 
0.1%
2021-04-15T01:08:12.495556image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:12.552380image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103588
99.9%
1.064
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0207240
66.6%
.103652
33.3%
164
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207240
> 99.9%
164
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207240
66.6%
.103652
33.3%
164
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207240
66.6%
.103652
33.3%
164
 
< 0.1%

index__org:resource_0_9.0
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
102933 
1.0
 
719

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0102933
99.3%
1.0719
 
0.7%
2021-04-15T01:08:12.691811image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:12.745408image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0102933
99.3%
1.0719
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0206585
66.4%
.103652
33.3%
1719
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0206585
99.7%
1719
 
0.3%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0206585
66.4%
.103652
33.3%
1719
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206585
66.4%
.103652
33.3%
1719
 
0.2%

index__org:resource_0_other
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103650 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%
2021-04-15T01:08:12.891962image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:12.945414image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207302
> 99.9%
12
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

index__lastSent_0_missing
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
1.0
103652 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0
ValueCountFrequency (%)
1.0103652
100.0%
2021-04-15T01:08:13.083351image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:13.135681image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
1.0103652
100.0%

Most occurring characters

ValueCountFrequency (%)
1103652
33.3%
.103652
33.3%
0103652
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
1103652
50.0%
0103652
50.0%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
1103652
33.3%
.103652
33.3%
0103652
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
1103652
33.3%
.103652
33.3%
0103652
33.3%

index__notificationType_0_missing
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
1.0
103652 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0
ValueCountFrequency (%)
1.0103652
100.0%
2021-04-15T01:08:13.268223image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:13.320993image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
1.0103652
100.0%

Most occurring characters

ValueCountFrequency (%)
1103652
33.3%
.103652
33.3%
0103652
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
1103652
50.0%
0103652
50.0%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
1103652
33.3%
.103652
33.3%
0103652
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
1103652
33.3%
.103652
33.3%
0103652
33.3%

index__dismissal_0_4
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103650 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%
2021-04-15T01:08:13.453482image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:13.506955image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207302
> 99.9%
12
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

index__dismissal_0_@
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103643 
1.0
 
9

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103643
> 99.9%
1.09
 
< 0.1%
2021-04-15T01:08:13.646324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:13.700060image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103643
> 99.9%
1.09
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207295
66.7%
.103652
33.3%
19
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207295
> 99.9%
19
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207295
66.7%
.103652
33.3%
19
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207295
66.7%
.103652
33.3%
19
 
< 0.1%

index__dismissal_0_C
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103650 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%
2021-04-15T01:08:13.841618image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:13.896279image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207302
> 99.9%
12
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

index__dismissal_0_D
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103650 
1.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%
2021-04-15T01:08:14.036727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:14.090901image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103650
> 99.9%
1.02
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207302
> 99.9%
12
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207302
66.7%
.103652
33.3%
12
 
< 0.1%

index__dismissal_0_NIL
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
1.0
103636 
0.0
 
16

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0
ValueCountFrequency (%)
1.0103636
> 99.9%
0.016
 
< 0.1%
2021-04-15T01:08:14.234943image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:14.289423image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
1.0103636
> 99.9%
0.016
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0103668
33.3%
.103652
33.3%
1103636
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0103668
50.0%
1103636
50.0%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0103668
33.3%
.103652
33.3%
1103636
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0103668
33.3%
.103652
33.3%
1103636
33.3%

index__dismissal_0_other
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size809.9 KiB
0.0
103651 
1.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters310956
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103651
> 99.9%
1.01
 
< 0.1%
2021-04-15T01:08:14.429887image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-04-15T01:08:14.486737image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103651
> 99.9%
1.01
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0207303
66.7%
.103652
33.3%
11
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number207304
66.7%
Other Punctuation103652
33.3%

Most frequent character per category

ValueCountFrequency (%)
0207303
> 99.9%
11
 
< 0.1%
ValueCountFrequency (%)
.103652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common310956
100.0%

Most frequent character per script

ValueCountFrequency (%)
0207303
66.7%
.103652
33.3%
11
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII310956
100.0%

Most frequent character per block

ValueCountFrequency (%)
0207303
66.7%
.103652
33.3%
11
 
< 0.1%

Interactions

2021-04-15T01:07:10.199325image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:10.335204image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:10.468060image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:10.599927image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:10.737507image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:10.864105image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:10.985264image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:11.110424image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:11.239216image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:11.370449image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:11.494002image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:11.618254image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:11.747076image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:11.880261image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:12.004262image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:12.128912image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:12.261198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:12.400629image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:12.534394image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-04-15T01:07:12.666049image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2021-04-15T01:08:14.858548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-04-15T01:08:19.226578image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-04-15T01:08:23.573698image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-04-15T01:08:27.912966image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-04-15T01:08:32.115003image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-04-15T01:07:14.123303image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
A simple visualization of nullity by column.
2021-04-15T01:07:27.345172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

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